Pengembangan Sistem Multisensor Berbasis IoT untuk Pemantauan Kelembapan Tanah dan Kondisi Iklim Mikro secara Real-Time pada Budidaya Cabai
Abstract
Chili cultivation is highly sensitive to fluctuations in soil moisture and local microclimate, while manual observation provides limited temporal resolution for irrigation decisions. This study developed and evaluated an Internet of Things (IoT)-based multisensor system for real-time monitoring of soil moisture and microclimate conditions in chili cultivation. The prototype integrates an ESP32 DevKit V1 as the processing and communication unit, a Capacitive Soil Moisture Sensor V2 for soil moisture measurement, a DHT22 for air temperature and relative humidity, and a DS18B20 for soil temperature. Sensor readings are processed locally, displayed through an LCD interface, and transmitted through a wireless network to an IoT monitoring platform. A quantitative experimental approach was used to evaluate sensor response under dry, moist, and wet soil conditions and to characterize microclimate measurements. The soil moisture tests produced mean readings of 8.33% for dry soil, 63.00% for moist soil, and 97.67% for wet soil, demonstrating clear separation among the predefined moisture classes. Soil temperature measurements ranged from 27–31 °C with a mean of 28.8 °C, while DHT22 measurements produced a mean air temperature of 29.6 °C and relative humidity of 60.6%. These results indicate that the multisensor architecture can provide continuous, interpretable environmental information for chili cultivation. The system offers a practical foundation for data-driven irrigation management and can be extended with automated actuation, cloud analytics, and predictive models. The integrated approach reduces dependence on periodic manual inspection and supports timely identification of moisture deviations early.
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References
Sugiyono. (2019). Metode penelitian kuantitatif, kualitatif, dan R&D (2nd ed.). Alfabeta.
Anoop, E. G., & Bala, G. J. (2023). IoT and ML-based automatic irrigation system for smart agriculture system. Agronomy Journal, 116(3), 1187–1203. https://doi.org/10.1002/agj2.21344
Abioye, E. A., Hensel, O., Esau, T. J., Olakunle, E., Abidin, M. S. Z., Ayobami, A. S., Yerima, O., & Nasirahmadi, A. (2022). Precision irrigation management using machine learning and digital farming solutions. AgriEngineering, 4(1), 70–103. https://doi.org/10.3390/agriengineering4010006
Bakthavatchalam, K., Karthik, B., Thiruvengadam, V., Muthal, S., Jose, D., Kotecha, K., & Varadarajan, V. (2022). IoT framework for measurement and precision agriculture: Predicting the crop using machine learning algorithms. Technologies, 10(1), 13. https://doi.org/10.3390/technologies10010013
Ranjan, P., & Saini, V. (2022). Smart irrigation system using IoT. In Agri-Food 4.0: Innovations, challenges and strategies. Emerald Publishing. https://doi.org/10.1108/S1877-636120220000027009
Ramachandran, V., Ramalakshmi, R., Kavin, B. P., Hussain, I., Almaliki, A. H., Almaliki, A. A., Elnaggar, A. Y., & Hussein, E. E. (2022). Exploiting IoT and its enabled technologies for irrigation needs in agriculture. Water, 14(5), 719. https://doi.org/10.3390/w14050719
Phasinam, K., Kassanuk, T., Shinde, P. P., Thakar, C. M., Sharma, D. K., Mohiddin, M. K., & Rahmani, A. W. (2022). Application of IoT and cloud computing in automation of agriculture irrigation. Journal of Food Quality, 2022, 1–8. https://doi.org/10.1155/2022/8285969
Togneri, R. M., dos Santos, D. F., Camponogara, G., Nagano, H., Custódio, G., Prati, R. C., Fernandes, S., & Kamienski, C. (2022). Soil moisture forecast for smart irrigation: The primetime for machine learning. Expert Systems with Applications, 207, 117653. https://doi.org/10.1016/j.eswa.2022.117653
Riyadi, M. (2023). Sistem cerdas untuk monitoring pengukuran suhu dan kelembapan tanah pada tanaman cabai berbasis Internet of Things (IoT) menggunakan aplikasi Telegram. Jurnal Teknologi Elektro, 14(2). https://doi.org/10.22441/jte.2023.v14i2.008
Shahab, H., Iqbal, M., Sohaib, A., Khan, F. U., & Waqas, M. (2024). IoT-based agriculture management techniques for sustainable farming: A comprehensive review. Computers and Electronics in Agriculture, 220, 108851. https://doi.org/10.1016/j.compag.2024.108851
Faqir, Y., Qayoom, A., Erasmus, E., Schutte-Smith, M., & Visser, H. G. (2024). A review on the application of advanced soil and plant sensors in the agriculture sector. Computers and Electronics in Agriculture, 226, 109385. https://doi.org/10.1016/j.compag.2024.109385
Preite, L., & Vignali, G. (2024). Artificial intelligence to optimize water consumption in agriculture: A predictive algorithm-based irrigation management system. Computers and Electronics in Agriculture, 223, 109126. https://doi.org/10.1016/j.compag.2024.109126
Hamouda, F., Puig-Sirera, À., Bonzi, L., Remorini, D., Massai, R., & Rallo, G. (2024). Design and validation of a soil moisture-based wireless sensors network for the smart irrigation of a pear orchard. Agricultural Water Management, 305, 109138. https://doi.org/10.1016/j.agwat.2024.109138
Dong, Y., Werling, B., Cao, Z., & Li, G. (2024). Implementation of an in-field IoT system for precision irrigation management. Frontiers in Water, 6, 1353597. https://doi.org/10.3389/frwa.2024.1353597
Dafonte, J., González, M. Á., Comesaña, E., Teijeiro, M. T., & Cancela, J. J. (2024). Soil water status monitoring system with proximal low-cost sensors and LoRa technology for smart water irrigation in woody crops. Sensors, 24(24), 8104. https://doi.org/10.3390/s24248104
Zhang, X., Feng, G., & Sun, X. (2024). Advanced technologies of soil moisture monitoring in precision agriculture: A review. Journal of Agriculture and Food Research, 18, 101473. https://doi.org/10.1016/j.jafr.2024.101473
Pascoal, D., Silva, N., Adão, T., Lopes, R. D., Peres, E., & Morais, R. (2024). A technical survey on practical applications and guidelines for IoT sensors in precision agriculture and viticulture. Scientific Reports, 14, 29793. https://doi.org/10.1038/s41598-024-80924-y
Romadan, D. P., Arinal, V., Sarimole, F. M., & Tundo, T. (2024). Prototipe sistem monitoring kelembapan tanah pada tanaman cabai berbasis Internet of Things dengan metode fuzzy logic menggunakan NodeMCU ESP8266, Blynk dan ThingSpeak. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 5(1), 130–140. https://doi.org/10.57152/malcom.v5i1.1600
Martani, A., Perdana, A. L., & Anugrah, M. (2025). Prototype of Internet of Things (IoT) and Android-based chilli plant watering monitoring and control tool. Journal of System and Computer Engineering, 6(1). https://doi.org/10.61628/jsce.v6i1.1601
Chourlias, A., Violos, J., & Leivadeas, A. (2025). Virtual sensors for smart farming: An IoT- and AI-enabled approach. Internet of Things, 32, 101611. https://doi.org/10.1016/j.iot.2025.101611
Shahab, H., Naeem, M., Iqbal, M., Aqeel, M., & Ullah, S. S. (2025). IoT-driven smart agricultural technology for real-time soil and crop optimization. Smart Agricultural Technology, 10, 100847. https://doi.org/10.1016/j.atech.2025.100847
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